Mobile-device data, non-motorized traffic monitoring, and estimation of annual average daily bicyclist and pedestrian flows

Abstract

People who walk and bike are the most vulnerable road users. However, understanding where they walk and bike requires continual data monitoring. Traditional methods rely on physical sensors in the infrastructure to detect the presence of pedestrians and bicyclists. However, these are expensive to deploy and only detect road users at the specific locations they are deployed. Instead, this study develops methods to use mobile phone based GPS data to estimate the number of bicyclists and pedestrians, and applies this methodology to the Twin Cities Metro area in Minnesota. The developed methodology is able to estimate average pedestrian and bicyclist volumes with relatively high accuracy.